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BMCBI
2010
152views more  BMCBI 2010»
14 years 9 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
POPL
1996
ACM
15 years 1 months ago
From Region Inference to von Neumann Machines via Region Representation Inference
Region Inference is a technique for implementing programming languages that are based on typed call-by-value lambda calculus, such as Standard ML. The mathematical runtime model o...
Lars Birkedal, Mads Tofte, Magnus Vejlstrup
INFORMS
1998
100views more  INFORMS 1998»
14 years 9 months ago
Feature Selection via Mathematical Programming
The problem of discriminating between two nite point sets in n-dimensional feature space by a separating plane that utilizes as few of the features as possible, is formulated as a...
Paul S. Bradley, Olvi L. Mangasarian, W. Nick Stre...
FLAIRS
2006
14 years 11 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
BIOCOMP
2008
14 years 11 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...